Tyler Seibert, MD, Ph.D.
Radiation Oncologist | Assistant Professor
UC San Diego | Radiation Medicine | Radiology | Bioengineering
Seminar Information
Prostate cancer is a major public health challenge and the second leading cause of cancer death among U.S. men. With early detection, this disease can be effectively treated and cured. However, current screening paradigms are fraught with false positives and overdiagnosis of indolent disease. Meanwhile, management of aggressive prostate cancer is often partially blind, based on an incomplete picture of the disease before treatment and suboptimal measurements of response after treatment. Quantitative tools are poised to address these challenges and improve prostate cancer care at multiple points: genetic-risk-stratified screening, more precise diagnostic imaging, and enhanced image-guided cancer treatment.
Dr. Tyler Seibert is an Assistant Professor at the University of California San Diego in the Departments of Radiation Medicine, Radiology, and Bioengineering. After receiving a BS in Bioengineering at UC Berkeley, he joined the NIH Medical Scientist Training Program at UC San Diego, earning his MD and a PhD in Bioengineering. He also completed a medical residency in Radiation Oncology at UC San Diego. He is a board-certified radiation oncologist specializing in the treatment of prostate cancer and brain tumors and serves on the National Comprehensive Cancer Network (NCCN) Guidelines Panel on Prostate Cancer Early Detection.
Dr. Seibert leads a research lab located in the Altman Clinical Translational Research Institute (ACTRI). His research program focuses on quantitative imaging and predictive genomics, both with application to improving the detection and treatment of cancer. He is a Prostate Cancer Foundation Young Investigator and recipient of a National Institute of Biomedical Imaging and Bioengineering (NIBIB) Career Development Award (K08). His lab is funded by the NIH (NCI and NIBIB), the American Society for Radiation Oncology, and the Prostate Cancer Foundation.